Instructions to use hf-tiny-model-private/tiny-random-Wav2Vec2ForXVector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-Wav2Vec2ForXVector with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForAudioXVector processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-Wav2Vec2ForXVector") model = AutoModelForAudioXVector.from_pretrained("hf-tiny-model-private/tiny-random-Wav2Vec2ForXVector") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cfacbfcfe9f6e4c5b0efeaa4e0db8953c148e32d521de758236cc07c774f912f
- Size of remote file:
- 165 kB
- SHA256:
- 91674555a5d775f363a8277bf90f69636441d6c2650889d0fc398fad9b0343ab
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